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Climate change is raising winter temperatures in the Northeastern United States, both expanding the range of an invasive pest, the hemlock woolly adelgid (HWA; Adelges tsugae), and threatening the survival of its host species, eastern hemlock (Tsuga canadensis). As a foundation species, hemlock trees underlie a distinct network of ecological, biogeochemical, and structural systems that will likely disappear as the HWA infestation spreads northward. Remote sensing can offer new perspectives on this regional transition, recording the progressive loss of an ecological foundation species and the transition of evergreen hemlock forest to mixed deciduous forest over the course of the infestation. Lidar remote sensing, unlike other remote sensing tools, has the potential to penetrate dense hemlock canopies and record HWA’s distinct impacts on lower canopy structure. Working with a series of lidar data from the Harvard Forest experimental site, these studies identify the unique signals of HWA impacts on vertical canopy structure and use them to predict forest condition. Methods for detecting the initial impacts of HWA are explored and a workflow for monitoring changes in forest structure at the regional scale is outlined. Finally, by applying terrestrial, airborne, and spaceborne lidar data to characterize the structural variation and dynamics of a disturbed forest ecosystem, this research illustrates the potential of lidar as a tool for forest management and ecological research.
Advisor: | Schaaf, Crystal |
Commitee: | Valencius, Conevery Bolton, Chen, Robert F., Orwig, David A., Cook, Bruce, Krause, Keith |
School: | University of Massachusetts Boston |
Department: | Envronmental Sciences/Environmental, Earth and Ocean Sciences (PhD) |
School Location: | United States -- Massachusetts |
Source: | DAI-B 81/12(E), Dissertation Abstracts International |
Source Type: | DISSERTATION |
Subjects: | Environmental science, Ecology, Remote sensing |
Keywords: | Disturbance, Forest, Hemlock woolly adelgid, Invasive, Lidar, Waveform |
Publication Number: | 27832444 |
ISBN: | 9798641069432 |